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Biology, Bioinformatics, Computer Science, or a related field • Strong programming skills in R and/or Python • Experience with analysis of single-cell sequencing data • Familiarity with spatial
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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& Brian Hargreaves. Partial list of applicable skills: Expertise in MRI physics Experience with raw MRI data management Experience with MRI reconstruction Clinical studies: data collection / analysis Pulse
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meetings Key Responsibilities: Development and implementation of study protocols Participant recruitment and collection of participant and laboratory data Statistical analysis of data Authorship
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. Electrophysiology and MRI Data Analysis of Patients with Lennox-Gastaut Syndrome About Us: Stanford Pediatric Epilepsy Research is at the forefront of research in neuroscience, focusing on understanding complex
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cognitive abilities, and how those developmental trajectories differ (and are similar) across contexts. Planned projects: The planned research will focus on analysis of data collected in a global multi-site
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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods
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, Tumor Immunology, Molecular Biology, Protein Biology, Mouse work, Flow Cytometry/FACS, LC-MS/MS, TCR- and RNA-seq, and AI analysis. Required Application Materials: CV, research summary, and published
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psychology or pediatric anesthesiology. In addition to core research activities, the fellowship emphasizes capacity-building in grant writing, manuscript preparation, advanced data analysis techniques, and the